AI for Retinal Disease Diagnosis: Transfer Learning and Vessel Segmentation

This research leverages established deep learning techniques (Xception and W-Net) for multi-disease retinal classification, offering a potentially robust diagnostic tool. The use of transfer learning suggests efficiency and potential for application across diverse datasets, but further validation with clinical data is needed.

• •Applies transfer learning with Xception for efficient retinal disease classification.
• •Employs W-Net for vessel segmentation, potentially improving accuracy.
• •Focuses on multi-disease classification, expanding diagnostic capabilities.